About the role
Location: Chennai, Guindy Department: IT Experience Level: 12+ years Employment Type: Full-time Job Summary: We are looking for an experienced Data Architect with strong expertise in both traditional RDBMS and modern Big Data systems. The ideal candidate will be responsible for designing and implementing robust, scalable, and secure data architectures that support both transactional and analytical workloads across hybrid environments. Key Responsibilities: • Design and maintain enterprise data architecture that integrates RDBMS (e.g., MySQL, SQL Server, PostgreSQL) with Big Data platforms (e.g., Hadoop, Spark, Kafka). MANDATORY. • Develop data models, data flow diagrams, and architecture blueprints for both OLTP and OLAP systems. • Experts in AWS data & analytics world and respective services • Lead the modernization of legacy data systems to cloud-native or hybrid data platforms. • Collaborate with data engineers, DBAs, analysts, and business stakeholders to gather requirements and deliver end-to-end data solutions. • Ensure data quality, governance, security, and compliance across all data platforms. • Optimize data storage, processing, and retrieval for performance and cost efficiency. • Evaluate and recommend tools and technologies for data integration, transformation, and analytics. Required Skills and Qualifications: • Bachelor’s or Master’s degree in Computer Science, Information Systems, or related field. Internal Internal • 8+ years of experience in data architecture, with hands-on experience in both RDBMS and Big Data environments. • Strong knowledge of relational databases ( SQL Server, MySQL, PostgreSQL). • Expertise in Big Data technologies: Hadoop, Spark, Hive, HBase, Kafka, etc. • Experience with cloud platforms (AWS & others) and cloud-native data services (e.g., Redshift SnowFlake). • Proficiency in data modeling, ETL/ELT design, and data warehousing concepts. • Familiarity with data governance tools and frameworks. • Strong problem-solving and communication skills. Preferred Qualifications: • Certifications in cloud or data technologies (e.g., AWS Certified Data Analytics & others). • Experience with data lakehouse architectures and modern data stack tools (e.g., dbt, Delta Lake, Apache Iceberg). • Knowledge of containerization and orchestration tools (e.g., Docker, Kubernetes, Airflow).